Literature Survey On Clustering Techniques

Clustering is the assignment of data objects (records) into groups (called clusters) so that data objects from the same cluster are more similar to each other than objects from different clusters. Clustering techniques have been discussed extensively in similarity search, segmentation, statistics, machine learning, trend analysis, pattern recognition and classification. Clustering methods can be classified in to partition methods, hierarchical methods, density based methods, grid based methods and model based methods. In this paper, the author would like to give review about clustering methods by taking some example for each classification.

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Resource Details

Provided by:
Iosrjournals
Topic:
Big Data
Format:
PDF